Ten years ago Responsible AI meant building responsibly. Today, with generative AI in every profession, responsibility rests with each of us as adopters. The Artificiality Institute’s Become More Essential with AI course reframed my approach, from boundary questions to adaptation states, helping me model exemplar collaboration and guide others.
What does it look like to teach with AI, not just about it? In redesigning my undergraduate course, I treated AI as a responsible teaching assistant. Guided by Anthropic’s 4D framework for AI Fluency, I explored how to delegate tasks, craft ethical prompts, embed discernment into student work, and maintain full human oversight. This post shares the strategies, safeguards, and surprises behind building an AI-integrated course without compromising critical thinking or student agency.
Introducing generative AI to engineers in a concise session highlighted the importance of mindset over mere technical demonstration.
Drawing parallels between AI usage and adolescent curiosity, this post emphasizes the importance of responsible prompting and ethical considerations in AI adoption.
Exploring AI’s role in market research, this post details an experiment assessing AI’s capability to assist in brainstorming, structuring, and analyzing market insights effectively.
A little over a month ago, I set out to take a more focused approach to understanding Large Language Models (LLMs). I used them daily for everyday tasks—summarizing articles, refining emails, creating images—but I wanted to go deeper, with the new and powerful models that are now available. I wanted to answer a fundamental question:…